FPGA for Machine learning Applications
The merging growth in information handling technology that enables
the developers to understand the activity, evaluate the pattern and detect the
anomalies using Machine Learning algorithms in almost all industries. We need
high speed processing platforms at the other end to handle these data generated
features and ensemble various other platforms too.
The FPGA are High speed, configurable platforms that can adopt the fast twisted operation speeds within the single integrated SOC. Many semiconductor manufacturing industries are focused on developing the artificial intelligence AI sensors that stacked inside the SOC modules itself to help the ML developers utilize such IP cores for real time predictions.
These companies also incorporate references, design protocols, neural network IP cores, Software development tools and customized design services within the single SOC platforms. These FPGAs are high in performance, low power(starting from 1mW to 1W), flexible architecture and 5.5.mm package available [1] (ref. Lattice semiconductor)
The integrated FPGA accelerators helpful in developing lots of Smart applications enabled with machine learning frameworks. Where the data is larger, the device could take over the processing capability using the in-built accelerators. These devices are nowadays hardware adoptable and software adoptable too. evaluation of Tensor flow modules for training are accessed with the integrated environment itself.
Write to us for your machine learning based Research works qmostech@gmail.com
#qmostechnologies
#vlsiprojectsinchennai
https://www.facebook.com/vlsiprojectsinchennai/
Links: vlsiprojectsinchennai, #machinelearningprojectsinchennai
References
[1] https://www.latticesemi.com/en/Solutions/Solutions/SolutionsDetails02/sensAI
